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Special Issue "Heat and Mass Transfer in Multiphase Flows"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "J1: Heat and Mass Transfer".

Deadline for manuscript submissions: 10 July 2023 | Viewed by 613

Special Issue Editors

Research Institute of Mechanical Engineering. Department of Vibration Testing and Equipment Condition Monitoring, South Ural State University, Lenin prospect 76, Chelyabinsk 454080, Russia
Interests: heat and mass transfer; multiphase flows; Reynold number; high speed flows; industrial flows
Department of Chemical Engineering, Pakistan Institute of Engineering & Applied Sciences (PIEAS), Islamabad P.O. Box 46000, Pakistan
Interests: heat and mass transfer; multiphase flows; Reynold number; high speed flows; industrial flows
Chemical Engineering Discipline, School of Engineering, University of KwaZulu-Natal, Durban, South Africa
Interests: heat and mass transfer; multiphase flows; Reynold number; high speed flows; industrial flows

Special Issue Information

Dear Colleagues,

Recent years have witnessed significant increases in both applications as well as intensification of process systems involving multiphase flows. However, the interaction of these forces in the presence of internal and external forces results in a variety of transport mechanisms that are yet not clearly understood. The aim of this special issue is to provide a unified platform to the research community working in the domain of these multiphase flows (analytically, experimentally as well as computationally) to present their state-of-the-art works dealing with the interaction of more than one fluid phase from industrial as well as lab-scale equipment with special reference to the heat (energy) and mass transfer. Manuscripts dealing with energy conversion systems will be of special interest. The systems under consideration can be from the fossil-fueled energy industry, nuclear power section, HVAC and so on. The articles can be original research articles as well as state-of-the-art review articles.                   

The experimental, and theoretical investigations of the heat and mass transfer rates in condensation of steam processes are significant issues associated with a design of a wide range of industrial operations. This special issue of Energies Journal will include articles, which will cover topics, on steam flow and condensation; Up/Down steam injection into water with different configurations of steam jets including sub-sonic, sonic and superheated; shock wave/steam jet interaction and other relevant topics involving energy transformations and consumption. Also, to model the physical characteristics of steam jet interaction with the water (or other liquids, e.g., saline) as well as the condensation rates, it can be useful to implement the utilization of source values of physical dimensionless parameters such as Reynolds number (Reo), Plume Richardson number (Ripo), entrainment coefficient (αo), buoyant vertical scale (Bo) and others. In addition, the implication of physical modeling related to the geophysics flows involving the injection of a heated fluid(s) into the cooled fluid, is to characterize the radial spreading of the steam plumes in condensed water.

Dr. Afrasayab Khan
Prof. Dr. Atta Ullah
Dr. Khairuddin Sanaullah
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • heat and mass transfer
  • multiphase flows
  • Reynold number
  • high-speed flows
  • industrial flows
  • energy utilization
  • energy transformations

Published Papers (1 paper)

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Research

Article
Comparison of Standalone and Hybrid Machine Learning Models for Prediction of Critical Heat Flux in Vertical Tubes
Energies 2023, 16(7), 3182; https://doi.org/10.3390/en16073182 - 31 Mar 2023
Viewed by 438
Abstract
Critical heat flux (CHF) is an essential parameter that plays a significant role in ensuring the safety and economic efficiency of nuclear power facilities. It imposes design and operational restrictions on nuclear power plants due to safety concerns. Therefore, accurate prediction of CHF [...] Read more.
Critical heat flux (CHF) is an essential parameter that plays a significant role in ensuring the safety and economic efficiency of nuclear power facilities. It imposes design and operational restrictions on nuclear power plants due to safety concerns. Therefore, accurate prediction of CHF using a hybrid framework can assist researchers in optimizing system performance, mitigating risk of equipment failure, and enhancing safety measures. Despite the existence of numerous prediction methods, there remains a lack of agreement regarding the underlying mechanism that gives rise to CHF. Hence, developing a precise and reliable CHF model is a crucial and challenging task. In this study, we proposed a hybrid model based on an artificial neural network (ANN) to improve the prediction accuracy of CHF. Our model leverages the available knowledge from a lookup table (LUT) and then employs ANN to further reduce the gap between actual and predicted outcomes. To develop and assess the accuracy of our model, we compiled a dataset of around 5877 data points from various sources in the literature. This dataset encompasses a diverse range of operating parameters for two-phase flow in vertical tubes. The results of this study demonstrate that the proposed hybrid model performs better than standalone machine learning models such as ANN, random forest, support vector machine, and data-driven lookup tables, with a relative root-mean-square error (rRMSE) of only 9.3%. We also evaluated the performance of the proposed hybrid model using holdout and cross-validation techniques, which demonstrated its robustness. Moreover, the proposed approach offers valuable insights into the significance of various input parameters in predicting CHF. Our proposed system can be utilized as a real-time monitoring tool for predicting extreme conditions in nuclear reactors, ensuring their safe and efficient operation. Full article
(This article belongs to the Special Issue Heat and Mass Transfer in Multiphase Flows)
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